SkOTaPA: A Dataset for Skepticism Detection in Online Text after Persuasion Attempt

Abstract

Individuals often encounter persuasion attempts, during which a persuasion agent aims to persuade a target to change the target’s emotions, beliefs, and behaviors. These persuasion attempts can be observed in various social settings, such as advertising, public health, political campaigns, and personal relationships. During these persuasion attempts, targets generally like to preserve their autonomy, so their responses often manifest in some form of resistance, like a skeptical reaction. In order to detect such skepticism in response to persuasion attempts on social media, we developed a corpus based on consumer psychology. In this paper, we consider one of the most prominent areas in which persuasion attempts unfold: social media influencer marketing. In this paper, we introduce the skepticism detection corpus, SkOTaPA, which was developed using multiple independent human annotations, and inter-coder reliability was evaluated with Krippendorff’s alpha (0.709). We performed validity tests to show skepticism cannot be detected using other potential proxy variables like sentiment and sarcasm.